Datasets:

---

ItsMaxNorm

/

pc-research

like 0

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
links: struct<papers: list<item: struct<title: string, url: string, pdf_url: string, doi_url: string, source: string, year: int64>>, by_source: struct<offline_iclr: list<item: struct<title: string, url: string, pdf_url: string, doi_url: null, source: string, year: int64>>, offline_nips: list<item: struct<title: string, url: string, pdf_url: string, doi_url: null, source: string, year: int64>>, offline_icml: list<item: struct<title: string, url: string, pdf_url: string, doi_url: null, source: string, year: int64>>, offline_cvpr: list<item: struct<title: string, url: string, pdf_url: string, doi_url: null, source: string, year: int64>>, semantic_scholar: list<item: struct<title: string, url: string, pdf_url: string, doi_url: string, source: string, year: int64>>, arxiv: list<item: struct<title: string, url: string, pdf_url: string, doi_url: null, source: string, year: int64>>>, pdfs_only: list<item: struct<title: string, pdf: string>>, dois_only: list<item: struct<title: string, doi: string>>>
metadata: struct<query: string, total_steps: int64, last_updated: string, started_at: string, total_papers: int64>
vs
papers: list<item: struct<title: string, authors: list<item: string>, abstract: string, url: string, year: int64, venue: string, source: string, doi: string, pdf_url: string, citations: int64, categories: list<item: string>, id: string, track: string, status: string, keywords: string, tldr: string, primary_area: string, similarity_score: double, novelty_score: double, recency_score: double, relevance_score: double, bm25_score: double, combined_score: double, rank: int64>>
metadata: struct<query: string, total_steps: int64, last_updated: string, started_at: string, total_papers: int64>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3608, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2368, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2573, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2060, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2082, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 572, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              links: struct<papers: list<item: struct<title: string, url: string, pdf_url: string, doi_url: string, source: string, year: int64>>, by_source: struct<offline_iclr: list<item: struct<title: string, url: string, pdf_url: string, doi_url: null, source: string, year: int64>>, offline_nips: list<item: struct<title: string, url: string, pdf_url: string, doi_url: null, source: string, year: int64>>, offline_icml: list<item: struct<title: string, url: string, pdf_url: string, doi_url: null, source: string, year: int64>>, offline_cvpr: list<item: struct<title: string, url: string, pdf_url: string, doi_url: null, source: string, year: int64>>, semantic_scholar: list<item: struct<title: string, url: string, pdf_url: string, doi_url: string, source: string, year: int64>>, arxiv: list<item: struct<title: string, url: string, pdf_url: string, doi_url: null, source: string, year: int64>>>, pdfs_only: list<item: struct<title: string, pdf: string>>, dois_only: list<item: struct<title: string, doi: string>>>
              metadata: struct<query: string, total_steps: int64, last_updated: string, started_at: string, total_papers: int64>
              vs
              papers: list<item: struct<title: string, authors: list<item: string>, abstract: string, url: string, year: int64, venue: string, source: string, doi: string, pdf_url: string, citations: int64, categories: list<item: string>, id: string, track: string, status: string, keywords: string, tldr: string, primary_area: string, similarity_score: double, novelty_score: double, recency_score: double, relevance_score: double, bm25_score: double, combined_score: double, rank: int64>>
              metadata: struct<query: string, total_steps: int64, last_updated: string, started_at: string, total_papers: int64>